Acoustic modelling of surface sources. Part I. Piston model, discretizing error, axisymmetrical problem by A. BRAŃSKI

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Error Analysis and Artificial Intelligence: Preliminary exploration of English as a Foreign Language written productions by Manuel Macías-Borrego

“…Among other findings, error elimination was observed in more than 70% of the cases and a better application of grammatical rules in more than 75%. …”
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Using ORRT Models for Mean Estimation under Nonresponse and Measurement Errors in Stratified Successive Sampling by Monica Choudhary, Sanam Preet Kour, Sunil Kumar, Carlos N. Bouza, Agustín Santiago

“…Theoretical results have been verified through a simulation study using an artificial population and two real-life applications. With the outcomes of the proposed estimator, a suitable recommendation has been made to the survey statisticians for their real-life application.…”
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Enhanced Model Predictive Control Using State Variable Feedback for Steady-State Error Cancellation by Marcos Andreu, Jaime Rohten, José Espinoza, José Silva, Esteban Pulido, Lesyani Leon

“…This document presents a predictive control scheme augmented with integral state feedback tailored to a photovoltaic (PV) application. In scenarios with uncertain system parameters, steady-state errors can particularly impact reactive power regulation, where the absence of an integral term in the loop exacerbates this issue. …”
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Dynamic Partial Reconfiguration Project for the Anti-single Event Effect Based on the Soft Error Mitigation by XIE Da;DONG Yiping;WANG Lan;CAO Jinde;GUO Junjie

“…At the same time, the local error correction and the dynamic reconfiguration are employed in the system to restrain. …”
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Energy Efficient and High Speed Error Control Scheme for Real Time Wireless Sensor Networks by Ali Barati, Ali Movaghar, Masoud Sabaei

“…In this paper, a novel energy efficient and high speed error control scheme is introduced that is based on the Redundant Residue Number System (RRNS) allowing real-time application of WSNs. …”
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Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error by Jianhui Zhao, Erqian Dong, Mingui Sun, Wenyan Jia, Dengyi Zhang, Zhiyong Yuan

“…A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. …”
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Generation of Phase-Only Fourier Hologram Based on Double Phase Method and Quantization Error Analysis by Yang Wu, Jun Wang, Chun Chen, Chan-Juan Liu, Feng-Ming Jin, Yu-Hen Hu

“…However, it cannot directly encode the Fourier spectrum because of the limited gray modulation range of spatial light modulator, and quantization error. This shortage restricts the application of the double phase in the phase-only Fourier hologram, and this issue is never discussed, and solved as far as we know. …”
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A Rectal Cancer Surgery Dataset: Use of artificial intelligence to aid automation of error identification by Walaa Ghamrawi, Nathan Curtis, Jialang Xu, Matt Boal, Evangelos Mazomenos, Eddie Edwards, Danail Stoyanov, Nader Francis

“…The OCHRA methodology involved segmentation of the 77 operations and manually annotating each case for the enacted errors and near misses. We provide a detailed description of the errors and near misses of over 380 hours of video analysis, containing 1377 errors. …”
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Phase Error Correction in Sparse Linear MIMO Radar Based on the Equivalent Phase Center Principle by Wenyuan Shao, Jianmin Hu, Yicai Ji, Jun Pan, Guangyou Fang

“…Array sparse optimization reduces the hardware cost of MIMO radar, while virtual aperture and the equivalent phase center (EPC) principle simplify the radar signal model and reduce the computation and complexity of imaging algorithms. However, the application of sparse array structure and the EPC principle produces a non-negligible phase error, which affects the imaging quality. …”
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Analysis of Requirements and the Feasible Limit for Error Reduction in Two-Parameter Magnetic Determination of Steels’ Hardness by S. G. Sandomirski

“…However, the specific conditions and requirements for application of the two-parameter methods remain unclear. …”
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National competition reveals common errors in target delineation among young clinicians in radiation therapy by Qingyu Huang, Xue Dou, Jing Liu, Rui Feng, Xiang Zhang, Jinbo Yue

“…Abstract Background Radiation therapy's efficacy hinges on accurate tumor and organ delineation, a task currently dependent on manual methods prone to high variability and error. To address this, we organized a national targeting competition to identify and rectify common targeting errors among young clinicians. …”
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Dealing with AFLP genotyping errors to reveal genetic structure in Plukenetia volubilis (Euphorbiaceae) in the Peruvian Amazon. by Jakub Vašek, Petra Hlásná Čepková, Iva Viehmannová, Martin Ocelák, Danter Cachique Huansi, Pavel Vejl

“…Nonetheless, these techniques are not absolutely reliable because of various sources of errors arising during the genotyping process. Thus, a complex analysis of genotyping error was carried out with the AFLP method in 169 samples of the oil seed plant Plukenetia volubilis L. from small isolated subpopulations in the Peruvian Amazon. …”
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Offshore Wind Farm Wake Deflection Control Based on Adaptive Wind Condition Prediction Error by Jie YAN, Jialin YANG, Hangyu WANG, Jiaoyang LU, Yongqian LIU, Lei ZHANG

“…The wind prediction is an important input to the wind farm wake deflection control, and its error has a huge impact on the actual control effect, even leading to a "decrease instead of an increase" in the overall power generation, which greatly limits the engineering application of wind farm wake deflection control technology. …”
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On the Exact Asymptotic Error of the Kernel Estimator of the Conditional Hazard Function for Quasi-Associated Functional Variables by Abdelkader Rassoul, Abderrahmane Belguerna, Hamza Daoudi, Zouaoui Chikr Elmezouar, Fatimah Alshahrani

“…By employing kernel smoothing techniques and asymptotic analysis, we derive the exact asymptotic expression for the leading terms of the quadratic error, providing a precise characterization of the estimator’s convergence behavior. …”
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A Review of Machine Learning-Based Thermal Error Modeling Methods for CNC Machine Tools by Sen Mu, Chunping Yu, Kunlong Lin, Caijiang Lu, Xi Wang, Tao Wang, Guoqiang Fu

“…The application of these two methods in thermal error modeling and compensation is reviewed and summarized in detail. …”
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Atmospheric Modulation Transfer Function Calculation and Error Evaluation for the Panchromatic Band of the Gaofen-2 Satellite by Zhengqiang Li, Mingjun Liang, Yan Ma, Yang Zheng, Zhaozhou Li, Zhenting Chen

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Array gain and phase calibration in the presence of multipath based on weighted spatial smoothing by WANG Bu-hong1, WANG Yong-liang2, CHEN Hui2

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Error Classification and Static Detection Methods in Tri-Programming Models: MPI, OpenMP, and CUDA by Saeed Musaad Altalhi, Fathy Elbouraey Eassa, Sanaa Abdullah Sharaf, Ahmed Mohammed Alghamdi, Khalid Ali Almarhabi, Rana Ahmad Bilal Khalid

“…Moreover, existing tools are inadequate for detecting such errors in tri-model applications, leaving a critical gap in development support. …”
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Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition by Rong Wang

“…Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. …”
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